Data collected from smartphone embedded sensors will be transmitted to a secure server, where it can be analyzed. Using data comparison from a control group of healthy people, algorithms will be developed to gauge the severity of symptoms, and distinguish different movement disorders from one another.

Jean-Francois Daneault, an assistant professor at Rutgers School of Health Professions, received a $400,000 research grant from the National Institutes of Health to use wearable and mobile data to diagnose and monitor movement disorders.

With the aging population, more people are living with movement disorders but there is a shortage of neurologists and movement disorder specialists trained to diagnose and manage treatment.

“We propose leveraging smartphones to help non-specialists in the diagnosis, monitoring and management of movement disorders that often exhibit overlapping symptoms, such as Essential Tremor, Parkinson’s disease, Huntington’s disease, and other functional movement disorders,” said Daneault.

Smartphone-based platforms will assess the severity of symptoms such as balance, gait, rest tremor, upper limb coordination and cognitive impairments.

Data collected from smartphone embedded sensors will be transmitted to a secure server, where it can be analyzed. Using data comparison from a control group of healthy people, algorithms will be developed to gauge the severity of symptoms, and distinguish different movement disorders from one another.

Finally, the study will assess whether the smartphone platform is an effective way to monitor patients over the long-term. Patients will be asked to use the smartphone application at home to determine longer-term compliance.